Customer Relationships Get the Data Treatment

A new data tool from South Africa’s Nedbank helps its clients understand their customers’ shopping patterns.

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Competing With Data & Analytics

How does data inform business processes, offerings, and engagement with customers? This research looks at trends in the use of analytics, the evolution of analytics strategy, optimal team composition, and new opportunities for data-driven innovation.
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Many companies operate within a customer relationship data chain: That is, one company has the know-how — and the incentive — to help its customers understand their own customers better.

That’s certainly the case with banks that issue and manage credit cards. A new case study by MIT Sloan Management Review, “A Data-Driven Approach to Customer Relationships,” details how the South African bank Nedbank is using its rich access to a trove of transactional data from credit card use — from the time of transactions and size of purchases to retailer locations and even specific details like the age, gender, race, marital status, and income bracket of some users — to help merchants make strategic decisions to better serve those customers.

Among the highlights of the case study:

The bank realized that data it was already collecting was valuable — and not being used. The bank had accumulated a massive amount of data on debit and credit card transactions. Critically, the bank bet that this data could provide deep insights and be extremely valuable to the bank’s merchant clients in understanding their own businesses — and that it could, in fact, be better than the market data those merchants were already purchasing on the open market. That was because the bank had the ability to augment the payment data with Nedbank’s demographic data.

Nedbank had a strong incentive to develop a new data analytics tool for competitive differentiation. “Nedbank was operating in a difficult market,” writes MIT Sloan Management Review executive editor David Kiron. South Africa had a sluggish economy and a projected economic growth of only 0.1% in 2016. Nedbank issues debit and credit cards, offers point-of-sale card devices for merchants, and processes payments (termed “acquiring”) for merchants. Although the bank had a 20% share of South Africa’s acquiring market, a strategic review within the bank concluded that to sustain that business, the bank would have to enhance its value-added services. “It’s profitable, but [profit is maintained] through volume growth rather than margin growth,” says Sydney Gericke, head of Nedbank’s Card and Payments business. Translation: The bank knew that it had to keep its current customers and add new ones too.

With the new data tool, the bank’s merchant customers could have the ability to understand their customers in rich, new ways. The bank began offering a data analytics tool called Market Edge to its merchant clients in 2015. Market Edge packages credit and debit card information with geolocation, demographic, and other transactional data to allow insights into customer behavior. With the new tool, the hardware retailer BUCO, which has 46 locations across South Africa, was able to see patterns in what kinds of customers were visiting which stores and when. “We can now look at card transaction data and say, ‘On a Wednesday at 9 a.m., we had the most card transactions versus any other day in the week, and most of these people are [between] 50 and 60 years old,’” Judy Gounden, a group marketing executive at BUCO’s parent company, Iliad Africa Ltd., said in the case study. “When I told a store manager who believed that most of his business was derived from local residents that, in fact, half of his business was coming from residents that lived in a town 10 kilometers away, his eyes went wide and he said, ‘How do you know that?’ So we shared the data with him.” Simon Marland, Nedbank’s executive head of digital and business intelligence solutions, notes that for the bank’s merchant clients, “We’re telling them something about their business that nobody else has told them.”

Merchant customers also began receiving raw information for making strategic decisions. Pizza chain Andiccio 24 uses Market Edge’s geolocation data about where customers come from and how far they travel to better plan its retail expansion. The restaurant chain Cape Town Fish Market is requiring its franchisees to use Market Edge — to give the franchisees insight for operational and staffing-level decisions, and to give the corporate office broad oversight.

One challenge: Retailers don’t always know what to do with raw information. “We can’t just expect a retailer who is very good at knowing what shampoo should be on the shelf to see data and interpret it in a way that makes them change their business,” says Chris Wood, the bank’s head of emerging payments, strategy, and regulation. He sees an opportunity to add consulting services to the bank’s services mix. One idea: work with boutique consultancy firms that could package data into quarterly reports, and meet with Nedbank customers to help translate what the data says and what that means.

Still, the data tool has already been a game changer in merchant loyalty. “Where before they might have said, ‘your competitor made me a better offer, you need to match or I’m moving my business,’ now the issue is around value for the client,” says Wood. Jo Baliah-Coelho, head of digital product and innovation, says, “Our competitors have lost merchants who have moved to us for Market Edge.” And the potentials are large. After a nine-month pilot with 12 retailers before its July 2015 release, Market Edge is used at 1,500 locations today. So far Nedbank has targeted its very largest clients, which it is most anxious to lock in. Card and Payments chief Gericke wants to see 10,000 more merchant locations. Wood is more ambitious, aiming for 90,000 or almost half of the bank’s 200,000 business customers. “We’re selling something that people don’t yet know they want,” he says.

Topics

Competing With Data & Analytics

How does data inform business processes, offerings, and engagement with customers? This research looks at trends in the use of analytics, the evolution of analytics strategy, optimal team composition, and new opportunities for data-driven innovation.
More in this series

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